Volume 12 | Issue 2 |

 Abstract

The shift of business data and applications to the cloud has significantly enhanced security and threat detection capabilities. Traditional security strategies need to be reassessed to effectively safeguard against advanced threats in the delicate network infrastructures of cloud environments. Recognizing this challenge, artificial intelligence (AI) plays a crucial role in improving the precision and swiftness of threat identification and response. This study delves into the influence of AI on cloud security and threat detection. It explores the effective utilization of AI-based mechanisms in detecting attacks, drawing insights from more than 80 research papers. The analysis encompasses considerations of factors like the algorithms employed and performance metrics used for detection. The primary goal of this study is to furnish a comprehensive overview of various AI-based mechanisms in intrusion detection, providing valuable insights for future researchers to gain a deeper understanding of the challenges associated with multi-classification of attacks.

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 Keywords

Intrusion detection, Cloud, Supervised learning, Unsupervised learning

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Sign Language is mainly used by deaf (hard hearing) and dumb people to exchange information between their own community and with other people. It is a language where people use their hand gestures to communicate as they can't speak or hear. Sign Language Recognition (SLR) deals with recognizing the hand gestures acquisition and continues till text or speech is generated for corresponding hand gestures. Here hand gestures for sign language can be classified as static and dynamic. Deep Learning Computer Vision is used to recognize the hand gestures by building Deep Neural Network architectures (Convolution Neural Network Architectures) where the model will learn to recognize the hand gestures images over an epoch.

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 Keywords

Sign Language, CNN, Deep Learning, Communication

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Creative Commons Attribution 4.0 and The Open Definition

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Skin disease prediction and identification have long been difficult and crucial tasks for medical practitioners. Numerous clinics and skin care specialists charge outrageous prices for their services. The prevalence of skin conditions is widespread throughout our nation simultaneously. The majority of skincare professionals currently use time-consuming traditional methods to detect diseases, which may take a long period. Skin diseases have become important issues in recent years due to various environmental, socioeconomic, and dietary variables. This essay compares various skin illnesses regarding both cosmetics and common skin problems. A review of several publications is conducted based on the technologies employed, the accuracy of the results, the ethical behavior, the number of diseases identified, the datasets, etc.

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 Keywords

Artificial Intelligence, Deep Learning, Skin, Cosmetic, Diseases; Survey, Cosmetology, Intelligent System

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The study aims to provide empirical insights into the intricate determinants influencing investment decisions within these sectors, drawing from data collected from 250 working women. This quantitative analysis delves into the factors shaping the investment behavior of employed women in Uttar Pradesh, focusing on the education, information technology, healthcare, and banking sectors. Initial findings reveal variations in investment behavior across sectors. In the education sector, financial literacy and income significantly impact investment choices, while the information technology sector underscores the influence of income. Family responsibilities contribute to conservative investment choices in healthcare, and professional expertise emerges as a decisive factor in the banking sector. These sector-specific nuances highlight the multifaceted nature of investment decisions among employed women. The study underscores the importance of tailored financial education initiatives for each sector and suggests a need for interventions and products aligned with diverse investment preferences, targeting policymakers and financial institutions. This research contributes valuable insights into the complex landscape of investment behavior among working women in Uttar Pradesh.

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 Keywords

Investment behavior, working women, financial literacy, income levels, risk tolerance, sector-specific influences.

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In the ever changing world of luxury brands, consumer perception has a significant impact on how the market functions for luxury brands. This study aims to explore the intricate relationship between marketing strategies employed by premium brands and consumer perceptions of luxury. Demand has been continuously on the rise for luxury products, especially among Gen Z.". Luxury brands have faced a paradigm shift in the past few years as traditional marketers who believe in exclusivity and opulence are being challenged by new consumers who value sustainability, authenticity, and experiential elements more. Despite extensive research in the field of luxury brand marketing by academicians in recent years, different findings and opinions exist in regards to how it works and how one can utilize strategies effectively to create brand loyalty and improve brand perceptions. In this research, consumers perceptions about luxury products from an Indian perspective have been examined through a questionnaire that was carried out among respondents belonging to different social strata from selected cities in India.

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 Keywords

Luxury Brand, Consumer Perception, Marketing Strategies, luxury market.

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 Abstract

Interaction of substituted chalcone derivatives, 4-phenylbut-3-en-2-one, (E)-3-(4-hydroxyphenyl)-1-phenylprop-2-en-1-one and 3-(2-hydroxyphenyl)-1-phenylprop-2-en-1-one with the semiconductor nanoparticles such as TiO2 and ZnO were studied by UV-VIS absorption, fluorescence spectroscopy, FT-IR, and Cyclic Voltammetry. The Global chemical reactivity descriptor (GCRD) parameters, HOMO, LUMO, energy gap, and Molecular electrostatic potential (MESP) plots were obtained for the chalcone derivatives using DFT, B3LYP level, 6-311G basis set in Gaussian 09W. Benesi-Hildebrand plots were used to understand the stoichiometric interactions between chalcone derivative and semiconductor nanoparticles. All three chalcone derivatives exhibit fluorescence enhancement in the presence of semiconductor nanoparticles. Chalcone derivative, 3-(2-hydroxyphenyl)-1-phenylprop-2-en-1-one shows the selective response to TiO2 and ZnO in acetonitrile solvent. The energy gap value determined from Cyclic Voltammogram is very close to the value obtained from the DFT computation. From the spectroscopic and DFT computational study, these chalcone derivatives have potential applications in nonlinear optics.

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fluorescence enhancement; chalcone derivative; energy gap; chemical reactivity; computation

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Flood is one of the most devastating natural hazards affecting life and damaging properties, so we came up with an idea "Design Thinking based Enhanced Technology for flood threat protection using AI" in which we implement in 2 methods. One is by reducing the flood threat damage by constructing moveable walls in the downstream which at-least reduce the destruction damage by 20% by increasing the height of the with the aspects of flood and another method is to prevent life's from flood when it occurred, we deploy a bot which analyse the humans who struck in the flood and save them. Which will we in standby mode when in has flood threat alert so when flood occurs as much as possible the deployed bot can save lives from flood. This is an energy efficient and low power consumption bot which might be efficient in all aspects. The bot we deploy which detects the people using AI and through AI it predicts the high-risk zone where people have the probability of being struck.

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Flood, Design Thinking, AI, Bot, Low power consumption.

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: The provision of adequate drinking water has been the primary policy goal for many governments worldwide and has been one of the main policy agendas for a few decades (Adams,2018). However, the world's situation in providing safe and adequate water is sub-optimal, as recorded by numerous agencies. Nearly 771 million people do not have clean drinking water access and nearly a quarter do not have access to sufficient drinking water (WHO/UNICEF JMP, 2021). (Dharmapuri et.al-2022). The Government is committed to providing safe and adequate drinking water to all habitations by 2022. The National Rural Drinking Water Programme (NRDWP) has already provided 81.07 per cent rural habitations with access to 40 litres of drinking water per capita per day (LPCD) and another 15.58 per cent with partial access. The target is to provide piped water connection by 2024 under the recently launched Jal Jeevan Mission. The main objectives of this paper are to study the overall trends and patterns of drinking water facilities and analyse the household's accessibility and source of drinking water facilities among the social groups in rural Karnataka. To analyse the district-wise drinking water disparities in rural Karnataka. The study area covers the Karnataka region. This study primarily uses secondary data obtained from various sources, including Census 2001 and 2011 data, NFHS-4 and NFHS-5 data, and Karnataka Economic Survey reports. Statistical tools such as percentages, coefficients of variation (CV), and growth rates, as well as bar diagrams and charts, are utilised where necessary in the analysis.

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Key Words: Water Accessibility, Rural Households, Karnataka and Regional Disparity.

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The school environment plays a crucial role in shaping students overall well-being, encompassing various aspects such as their emotional, social, and mental health. One key determinant of student's well-being is the school climate, which refers to the quality and character of the school environment. The present study explores how the school climate affects the well-being of students while accounting for a few key well-being criteria, such as academic success, student involvement, social relationships, and mental health. The random sampling technique was used in the study to select a sample of 35 students in standard IX. Self-developed questionnaire was applied for collecting the relevant data The findings of study revealed that the schools were successful in creating a safe, valuable, meaningful, and comfortable environment for its students. Some students felt that there were limited opportunities for involvement in the decision-making process and expressed a desire for more opportunities to participate and have a voice in shaping their educational experience. It was also seen that schools did not neglect or overlook mental health issues, and they gave consideration for improvement in promoting a healthy work-life balance. There were concerns about the lack of respect and inclusivity among students, suggesting the need to address negative peer influences and foster a more inclusive and respectful social environment. The study concluded that a positive school climate is necessary for the well-being of the student community.

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 Keywords

School climate, Well-being

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Creative Commons Attribution 4.0 and The Open Definition

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In agricultural landscapes, the rhizosphere serves as a dynamic niche where plant-microbe interactions profoundly influence soil health and plant growth. Plant Growth-Promoting Rhizobacteria (PGPR) is pivotal contributor to soil fertility, nutrient cycling, and plant health. In the context of Bihar, India, rice cultivation holds paramount importance for food security and economic stability but faces challenges related to soil degradation and nutrient deficiency. Harnessing the potential of indigenous PGPR strains presents a promising strategy to enhance rice productivity sustainably. This research endeavors to explore the microbial diversity in the rhizospheric soil of rice fields in Bihar, focusing on isolating and characterizing potential PGPR strains. Through molecular and microbiological techniques, indigenous PGPR candidates are identified for their plant growth-promoting attributes, including nitrogen fixation, phosphate solubilization, and biocontrol capabilities. Biochemical and molecular analyses reveal diverse metabolic capacities and genetic relatedness of the isolates, with Azotobactor spp. exhibiting a notable 98.61% similarity to Bacillus tropicus. These findings underscore the potential of microbial biotechnology to enhance agricultural sustainability, foster food security, and mitigate environmental impacts, heralding innovative strategies for rice cultivation in Bihar and beyond.

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 Keywords

PGPR, rhizospheric soil, rice fields, isolation, characterization, functional assays, plant growth promotion

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